The original title is a "How I Built" style article title. I need to rewrite it as a news headline for a mobile feed.

Short summary

The author built a multi-agent AI research system using CrewAI that deliberately pauses before analysis, allowing humans to review findings and prevent hallucinations from propagating. The architecture separates concerns by agent responsibility, uses Docker for consistency, runs CI/CD checks, and optimizes costs with GPT-4o Mini. Core insight: production AI systems require human oversight, testing, observability, and good engineering—raw model intelligence alone is insufficient.

• •Multi-agent system with intentional human-in-the-loop validation prevents hallucination propagation
• •Separate agents by responsibility following Single Responsibility Principle for debuggability and scalability
• •Production reliability comes from engineering practices (Docker, CI/CD, testing) and cost optimization, not just intelligence

Generated with AI, which can make mistakes.